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app.py

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+import gradio as gr
+import requests
+import json
+import os
+import time
+from collections import defaultdict
+
+BASE_URL = "https://api.jigsawstack.com/v1"
+headers = {
+    "x-api-key": os.getenv("JIGSAWSTACK_API_KEY")
+}
+
+# Rate limiting configuration
+request_times = defaultdict(list)
+MAX_REQUESTS = 10  # Maximum requests per time window
+TIME_WINDOW = 60   # Time window in seconds
+
+def check_rate_limit(request: gr.Request):
+    """Check if the current request exceeds rate limits"""
+    if not request:
+        return True, "Rate limit check failed - no request info"
+    
+    ip = request.client.host
+    now = time.time()
+    
+    # Clean up old timestamps outside the time window
+    request_times[ip] = [t for t in request_times[ip] if now - t < TIME_WINDOW]
+    
+    # Check if rate limit exceeded
+    if len(request_times[ip]) >= MAX_REQUESTS:
+        time_remaining = int(TIME_WINDOW - (now - request_times[ip][0]))
+        return False, f"Rate limit exceeded. You can make {MAX_REQUESTS} requests per {TIME_WINDOW} seconds. Try again in {time_remaining} seconds."
+    
+    # Add current request timestamp
+    request_times[ip].append(now)
+    return True, ""
+
+def generate_embedding(input_type, text_content, url, content_type, token_overflow_mode, request: gr.Request):
+    """Generate embeddings using JigsawStack Embedding API with rate limiting"""
+    
+    # Check rate limit first
+    rate_limit_ok, rate_limit_msg = check_rate_limit(request)
+    if not rate_limit_ok:
+        return rate_limit_msg, ""
+    
+    # Validate inputs
+    if input_type == "Text" and not text_content:
+        return "Error: Please provide text content.", ""
+    if input_type == "URL" and not url:
+        return "Error: Please provide a URL.", ""
+    
+    try:
+        payload = {
+            "type": content_type,
+            "token_overflow_mode": token_overflow_mode
+        }
+        
+        if input_type == "Text":
+            payload["text"] = text_content.strip()
+        elif input_type == "URL":
+            payload["url"] = url.strip()
+        
+        response = requests.post(
+            f"{BASE_URL}/embedding",
+            headers=headers,
+            json=payload
+        )
+        response.raise_for_status()
+        result = response.json()
+        
+        if not result.get("success"):
+            error_msg = f"Error: API call failed - {result.get('message', 'Unknown error')}"
+            return error_msg, ""
+        
+        embedding = result.get("embeddings", [])
+        embedding_str = json.dumps(embedding, indent=2)
+        return "Embedding generated successfully!", embedding_str
+    except requests.exceptions.RequestException as e:
+        return f"Request failed: {str(e)}", ""
+    except Exception as e:
+        return f"An unexpected error occurred: {str(e)}", ""
+
+with gr.Blocks() as demo:
+    gr.Markdown("""
+        <div style='text-align: center; margin-bottom: 24px;'>
+            <h1 style='font-size:2.2em; margin-bottom: 0.2em;'>Vector Embedding Generator</h1>
+            <p style='font-size:1.2em; margin-top: 0;'>Generate vector embeddings from various content types including text, images, audio, and PDF files.</p>
+            <p style='font-size:1em; margin-top: 0.5em;'>Supported types: text, text-other, image, audio, pdf</p>
+            <p style='font-size:0.9em; margin-top: 0.5em; color: #666;'>Rate limit: {MAX_REQUESTS} requests per {TIME_WINDOW} seconds per IP</p>
+        </div>
+        """)
+    
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown("#### Content Input")
+            input_type = gr.Radio([
+                "Text",
+                "URL"
+            ], value="Text", label="Select Input Type")
+            
+            text_content = gr.Textbox(
+                label="Text Content",
+                placeholder="Enter the text content to generate embeddings for...",
+                visible=True,
+                lines=5
+            )
+            url = gr.Textbox(
+                label="URL",
+                placeholder="Enter the URL of the resource...",
+                visible=False
+            )
+            
+            content_type = gr.Dropdown(
+                choices=["text", "text-other", "image", "audio", "pdf"],
+                value="text",
+                label="Content Type",
+                info="Select the type of content being processed"
+            )
+            
+            token_overflow_mode = gr.Radio(
+                choices=["error", "truncate"],
+                value="error",
+                label="Token Overflow Mode",
+                info="How to handle input that exceeds token limits"
+            )
+            
+            generate_btn = gr.Button("Generate Embedding", variant="primary")
+            
+        with gr.Column():
+            gr.Markdown("#### Embedding Result")
+            status_message = gr.Textbox(label="Status", interactive=False)
+            embedding_result = gr.Textbox(
+                label="Vector Embedding",
+                interactive=False,
+                lines=15,
+                max_lines=25
+            )
+    
+    def toggle_inputs(selected):
+        if selected == "Text":
+            return gr.update(visible=True), gr.update(visible=False)
+        else:  # URL
+            return gr.update(visible=False), gr.update(visible=True)
+    
+    input_type.change(toggle_inputs, inputs=[input_type], outputs=[text_content, url])
+    
+    generate_btn.click(
+        generate_embedding,
+        inputs=[input_type, text_content, url, content_type, token_overflow_mode],
+        outputs=[status_message, embedding_result]
+    )
+
+demo.launch()

requirements.txt

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+gradio
+requests
+Pillow